The invention is in the field spectrum analyzers and is specifically in the field of real time digital spectrum analyzers.
Spectrum analyzers are widely used in many diverse fields, such as vibration studies, radar and sonar return analysis, speech studies and the like, where it is desirable to know the frequency content of signals.
Early types of spectrum analyzers are the so-called scanning analyzers which in effect look at an input signal through a narrow band filter to detect the frequency content of the input signal corresponding to the filter bandwidth. The filter may be tunable, or the effect of a tunable filter may be achieved by using a fixed filter in conjunction with a heterodyne system. A major disadvantage of the scanning analyzers is that the filter looks at only one spectral component at a time. If a great number of spectral components are of interest, the analysis time becomes prohibitively long.
In order to reduce the analysis time, the single filter of the scanning analyzer can be replaced by a bank of filters, each looking at a different spectral component. Analyzers employing filter banks are faster than single filter analyzers, but are generally inflexible and expensive.
In order to reduce the analysis expense and improve flexibility, recent types of spectrum analyzers have used the techniques of time compression analysis and Fast Fourier Transform analysis.
Time compression analyzers convert the input signal to digital form and store the digital representation of the input in a memory. The stored digital values are read out a number of times and are applied each time to a heterodyne system of the type discussed above, with the tuning oscillator of the heterodyne system being stepped through the frequency range of interest each time the memory contents are read out. Since the memory is generally read out much faster than the input signal is read into it, the analysis time can be reduced substantially. See, for example, U.S. Pat. No. 3,715,509.
In Fast Fourier Transform spectrum analysis, the so-called Cooley-Tukey algorithm is used to find the Discrete Fourier Transform of a sequence of numbers which represent the time history of an input signal. A specially programmed general purpose digital computer may be used, or a special purpose FFT machine can be used to carry out the Fast Fourier Transform analysis of a sequence of numbers. See, for example, U.S. Pat. No. 3,573,446 and U.S. Pat. No. 3,586,843.
The desirable characteristics of spectrum analyzers include flexibility, ease of operation, accuracy and low cost. While the recent types of time compression spectrum analyzers and Fast Fourier Transform analyzers meet certain aspects of these desirable characteristics, the need still remains for a spectrum analyzer which utilizes both time compression and Discrete Fourier Transform analysis, which is flexible to allow selected trade-offs between accuracy and speed, and which is easy to operate and uses such techniques and components for processing the input signal that its initial and operational costs are low.